Multi-Sensor Analysis of Global Daytime and Nighttime Urban Heat Islands

Steve Frolking, University of New Hampshire, steve.frolking@unh.edu (Presenter)
Jingfeng Xiao, University of New Hampshire, j.xiao@unh.edu
Annemarie Schneider, University of Wisconsin, aschneider4@wisc.edu
Thomas Milliman, Complex System Research Center, thomas.milliman@unh.edu
Leah Cheek, Boston University, leah_cheek@alumni.brown.edu
Mark Friedl, Boston University, friedl@bu.edu

Land conversion to urban uses has profound social and environmental impacts, with consequences for societal vulnerability to environmental stresses. For example, cities can experience deadly heat waves, amplified by the well-documented urban heat island (UHI) effect. As a result, climate change impact on urban populations has become a serious public health concern. However, modeling future urbanization and its interactions with climate change is in early development, and important datasets suffer from critical shortcomings. Existing global datasets are static snapshots, and do not represent disaggregated, detailed views of change, nor capture characteristics of the built environment most needed for surface parameterization in regional/global climate models. Satellite data, with consistent global coverage, can contribute substantially to the development of urban surface parameterization for climate models. We propose a multiplatform and sensor data fusion project to empirically evaluate a suite of global remote sensing data sets, representing a range of urban characteristics, against MODIS-derived land-surface temperature differences between urban and surrounding rural areas (i.e., the UHI). We will use two MODIS land surface temperature products (MYD11 and MOD21) to quantify urban heat islands globally over the MODIS era. The analysis will include two new urban datasets that we are developing - MODIS-derived change in global urban extent 2000-2010, and global urban microwave backscatter from SeaWinds on QuikScat - along with several MODIS standard products, DMSP/OLS nighttime lights data, and the new VIIRS Day/Night imagery. Our analysis will span a wide range of urban characteristics that likely influence the magnitude of daytime and/or nighttime UHIs - urban size, population density, building density, state of development, impervious fraction, vegetation cover, eco-climatic setting - and will examine a decade of rapid global urbanization, with wide geographic variation in recent rates of change in population, urban area, urban form, energy use, and economic development.

Presentation Type:  Poster

Session:  Theme 4: Human influence on global ecosystems   (Mon 4:30 PM)

Associated Project(s): 

• Related Activity: Related Activity or Previously Funded CC&E Activity not listed ...details

Poster Location ID: 61